Abstract

This study examines the implications of recent advances in global climate modelling for simulating storm surges. Following the ERA-Interim (0.75° × 0.75°) global climate reanalysis, in 2018 the European Centre for Medium-range Weather Forecasts released its successor, the ERA5 (0.25° × 0.25°) reanalysis. Using the Global Tide and Surge Model, we analyse eight historical storm surge events driven by tropical—and extra-tropical cyclones. For these events we extract wind fields from the two reanalysis datasets and compare these against satellite-based wind field observations from the Advanced SCATterometer. The root mean squared errors in tropical cyclone wind speed reduce by 58% in ERA5, compared to ERA-Interim, indicating that the mean sea-level pressure and corresponding strong 10-m winds in tropical cyclones greatly improved from ERA-Interim to ERA5. For four of the eight historical events we validate the modelled storm surge heights with tide gauge observations. For Hurricane Irma, the modelled surge height increases from 0.88 m with ERA-Interim to 2.68 m with ERA5, compared to an observed surge height of 2.64 m. We also examine how future advances in climate modelling can potentially further improve global storm surge modelling by comparing the results for ERA-Interim and ERA5 against the operational Integrated Forecasting System (0.125° × 0.125°). We find that a further increase in model resolution results in a better representation of the wind fields and associated storm surges, especially for small size tropical cyclones. Overall, our results show that recent advances in global climate modelling have the potential to increase the accuracy of early-warning systems and coastal flood hazard assessments at the global scale.

Highlights

  • Flooding of densely populated and low-lying coastal areas has large socio-economic impacts all around the world (Jongman et al 2012)

  • Coastal flooding is generally driven by storm surges which are caused by low mean-sea level pressure (MSLP) and strong 10-m winds (U10), such as those in tropical cyclones (TCs) and extratropical cyclones

  • Stopa and Cheung (2014) found a consistent low variability of ERAInterim in comparison to observations which is indicative of a model that is not able to capture extreme winds, and identified an average wind speed bias of − 10% for ERAInterims 99th percentile

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Summary

Introduction

Flooding of densely populated and low-lying coastal areas has large socio-economic impacts all around the world (Jongman et al 2012). Coastal flooding is generally driven by storm surges which are caused by low mean-sea level pressure (MSLP) and strong 10-m winds (U10), such as those in tropical cyclones (TCs) and extratropical cyclones. The surge component and the tidal component together make up the total water level (TWL) (Pugh 1996). Factors that determine the height of an extreme TWL and its impact are storm characteristics, tidal phase, bathymetry and coastline geometry. TCs can have lower MSLPs and stronger U10s than ETCs (Keller and DeVecchio 2016), resulting in a higher storm surge. ETCs are generally larger in size than TCs, thereby affecting a larger coastal area (Irish et al 2008).

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